1.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

1.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum       1.00       1.00
## LDevsum       1.00       1.02
## dh0           1.01       1.03
## dl0           1.19       1.66
## dl1           1.02       1.08
## dl2           1.18       1.64
## dl3           1.00       1.02
## 
## Multivariate psrf
## 
## 1.12

1.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

1.4 WAIC results

2.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

2.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum       1.00       1.00
## dh0           1.01       1.03
## 
## Multivariate psrf
## 
## 1.01

2.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

2.4 WAIC results

3.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

3.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## LDevsum       1.00       1.02
## dl0           1.19       1.66
## dl1           1.02       1.08
## dl2           1.18       1.64
## dl3           1.00       1.02
## 
## Multivariate psrf
## 
## 1.12

3.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

3.4 WAIC results